Multimodal physiological dataset from 15 subjects wearing chest and wrist sensors. Includes ECG, EDA, EMG, respiration, temperature, and accelerometry. CSV/pickle format. Used for stress detection and affective computing research.
Wearable IoT dataset with 18 physical activities from 9 subjects wearing 3 IMUs and a heart rate monitor. 54 columns including temperature, acceleration, and gyroscope data. CSV format. Used for HAR, activity classification, and intensity estimation.
Real-world wearable dataset from 15 nurses over one week in a hospital. Contains 11.5 million entries of EDA, heart rate, skin temperature, and orientation data collected via Empatica E4. CSV format. Used for occupational stress detection research.
Large-scale quality-assessed ICU PPG benchmark derived from MIMIC-III, with ECG, ABP, and respiration signals in 30-second WFDB segments. Multi-task format supporting cardiovascular and respiratory signal analysis for wearable algorithm development.
Residential smart-home power dataset with 2,075,259 one-minute measurements from a French household over 47 months. TXT/CSV-style tabular format. Used for load forecasting, NILM, and energy behavior analysis.
Smart-home energy dataset with detailed electrical, environmental, and operational streams from 3 real homes plus minute-level electricity data from 400+ homes. Open portal export format. Used for sustainable home and demand analysis.
Long-duration smart-home utility dataset with two years of minutely electricity, water, and natural gas measurements plus weather and billing data. CSV/TSV/RData formats. Used for forecasting, NILM, and resource analytics.
Appliance-level and aggregate electricity dataset from 20 UK households sampled every 8 seconds. CSV files, one per home. Built for energy conservation, NILM, demand response, and smart-home automation research.
Open-access domestic electricity dataset from 5 UK homes with whole-house demand at 16 kHz and appliance channels at 6-second intervals. Research-paper dataset release. Used for NILM, load disaggregation, and smart-meter analytics.